Mid-Market Energy & Utilities Company (representative) · Energy & Utilities · United States · 16 weeks
Asset and reporting data carried through S/4HANA with zero blackout
A representative engagement. The risk that scared leadership was losing reporting, not the ERP conversion itself. We modernized BW and protected continuity through cutover.
Challenge
A roughly 2,800-person energy and utilities company on SAP ECC ran operations off a sprawling BW estate built over a decade, with hundreds of objects, many unused, and extractors that would break against S/4HANA. Asset and equipment master data was inconsistent across systems. If reporting went dark during the migration, operations and compliance reporting would both suffer.
Approach
We combined a Blueprint and Readiness Assessment with BW modernization. We inventoried the estate, measured what was actually used, and retired the dead weight. We mapped every reporting dependency, re-pointed the extractors and models that mattered to the new S/4HANA structures, and validated reports reconciled to source. In parallel we cleansed and reconciled asset and equipment master data, and positioned the surviving estate for a future Datasphere foundation.
Outcome
Reporting continued through the migration with no blackout. The estate was far smaller and easier to run, the numbers reconciled to the migrated data, and the company had a defined route to modern analytics rather than a like-for-like lift.
Rationalize, do not lift
Most of the estate was unused. We measured real usage and retired the dead weight, so the company carried forward only what mattered instead of copying a decade of clutter into the new system.
Re-point and validate
We adapted the extractors and models that mattered to the new S/4HANA structures and validated that reports reconciled to source, so reporting kept working through the move.
A path to modern analytics
We positioned the surviving estate for a governed Datasphere foundation, so the migration became the moment analytics moved forward rather than a setback.
Results
- 16 wks Assessment, remediation, and BW modernization
- 2,100 to 680 BW objects, before and after rationalization
- Zero Reporting blackout days through the migration
- $1.3M Cost of a like-for-like BW lift avoided
Our biggest fear was going blind on operational reporting during cutover. It never happened. Thinklytics planned reporting continuity as part of the migration, retired years of clutter, and left us a foundation we can build on.
In the client's terms
The question
What stops reconciling the day we cut over?
The situation
An energy and utilities company of around 2,800 people ran operations off a BW estate built over a decade: hundreds of objects, many unused, and extractors that would break against S/4HANA. Asset and equipment master data was inconsistent across systems. A reporting blackout would have hit operations and compliance together.
What we found
Most of the estate was not load-bearing. The default plan was a like-for-like lift, which would have carried a decade of dead objects into the new platform at full cost and left the same problem to solve later.
What it produced
Reporting ran through the migration with zero blackout days. BW objects fell from 2,100 to 680, leaving an estate that is materially cheaper to run. The numbers reconciled to the migrated data, and the cost of a like-for-like lift, $1.3M, was avoided.
The roadmap
Assessment was combined with BW modernisation rather than sequenced after it. The estate was inventoried and measured by actual use, and the dead weight was retired before anything moved. Every reporting dependency was mapped, the extractors and models that mattered were re-pointed at the new S/4HANA structures, and reports were validated by reconciling to source. Asset and equipment master data was cleansed in parallel, and the surviving estate was positioned for a Datasphere foundation.
The work behind this result
- Our AI work is not delivering, the problem this engagement resolved.
- AI Readiness Assessment & Consulting
- Generative AI Consulting
- Managed Data Readiness Services
- AI Deployment Approval Pack, for whoever has to approve the spend.
- The 30 day Corporate Drag and Risk Diagnostic, findings yours either way.
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